Studying cooperative multi-agent reinforcement learning in networks by Oudah, Mayada Mohamed

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Multi-Agent Learning of Strategies in Abstract Argumentation Mechanisms by Nemer, Rama

“…The importance of this kind of work lies in the fact that it combines two aspects of multi-agent systems that have been quite separate to-date: argumentation protocols and multi-agent learning in games.…”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

“…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …”

Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm by Mostafa Jabari (21841727)

Fuzzy simulated evolution algorithm for VLSI cell placement by Sait, Sadiq M.

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Experimental evaluation of multi-agent reinforcement learning in real-world scale-free networks by Al Hashimi, Rashid

“…However, the study and analysis of the state-of-the-art multi-agent reinforcement learning (MARL) algorithms have been limited to small problems involving few number of learning agents.The purpose of this project is to conduct an extensive evaluation and comparison of MARL algorithms when used in networks that exhibit the scale-free property. …”
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A parallel tabu search algorithm for VLSI standard-cell placement by Suit, S.M.

“…In this work, tabu search placement algorithm is parallelized on a network of workstations using PVM. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…Given the complexity of the LDTP solution for managing online requests, we propose a real-time, lightweight solution using multi-agent meta-reinforcement learning. Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. …”

Genetic Algorithm Control Strategy for Heat Pump System in Battery Electric Buses by Al Haddad, Rabih

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Performance driven standard-cell placement using the geneticalgorithm by Youssef, H.

“…In this paper we present a timing-driven placer for standard-cell IC design. The placement algorithm follows the genetic paradigm. …”
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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm by Badreddine Kanouni (23073244)

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”

Adaptive cooperative control of nonlinear multi-agent systems with uncertain time-varying control directions and dead-zone nonlinearity by Maryam Shahriari-kahkeshi (17269051)

Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

“…Defensins are the type of AMPs that act as potential therapeutic drug agent and perform vital role in various biological process. …”

Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

“…This paper presents a reinforcement learning agent-based model that works by incorporating the MESA environment with the Stone Soup radar systems simulator. …”
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV by Zulkifli, Muhammad

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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer by D., Sathish Kumar

“…This study describes a residential thermal/electrical home energy system comprising a battery energy storage system and a combined heat and power fuel cell. The optimal planning of various energy resources is scheduled by a new optimization algorithm called Levy Flight and Chaos-assisted Artificial Rabbits Optimization (LFCARO), resulting in the lowest operational cost of this combined power system. …”
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